pandas dataframe export row column value - pandas

Question

I import data from Excel into python pandas with read_clipboard.
import pandas as pd
df = pd.read_clipboard()
The column index are the month (januar, februar, ...,december). The row index are products name (orange, banana, etc). And the value in cells are the monthly sales.
How can I export a csv of the following format
month;product;sales
To make it more visual, I show the input in the first image and how the output shoud be in the second image.

Answer 1

You can also use xlrd package.
Sample Book1.xlsx:
january february march
Orange 4 2 4
banana 2 6 3
apple 5 1 7
sample code:
import xlrd
book = xlrd.open_workbook("Book1.xlsx")
print(book.sheet_names())
first_sheet = book.sheet_by_index(0)
row1 = first_sheet.row_values(0)
print(first_sheet.nrows)
for i in range(len(row1)):
if i !=0:
next_row = first_sheet.row_values(i)
for j in range(len(next_row)-1):
print("{};{};{}".format(row1[i],next_row[0],next_row[j+1]))
Result:
january;Orange;4.0
january;Orange;2.0
january;Orange;4.0
february;banana;2.0
february;banana;6.0
february;banana;3.0
march;apple;5.0
march;apple;1.0
march;apple;7.0

Answer 2

If that is only the case, it might solve that problem:
month = df1.columns.to_list()*3
product = []
sales=[]
for x in range(0,2):
product += [df1.index[x]]*12
sales += df1.iloc[x].values.tolist()
df2 = pd.DataFrame({'month': month, 'product': product, 'sales': sales})
But you need to look for smarter way if you have a larger Dataframe, like what #Jon Clements suggested in the comment.

Answer 3

I finally solved it thanks to your advice : using unstack
df2 = df.transpose()
df3 = df2 =.unstack()
df3.to_csv('my/path/name.csv', sep=';')